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Purpose: Collagen features in breast tumor microenvironment is closely associated with the prognosis of patients. We aim to explore the prognostic significance of collagen features at breast tumor border by combining multiphoton imaging and imaging analysis. Methods: We used multiphoton microscopy (MPM) to label-freely image human breast tumor samples and then constructed an automatic classification model based on deep learning to identify collagen signatures from multiphoton images. We recognized three kinds of collagen signatures at tumor boundary (CSTB I-III) in a small-scale, and furthermore obtained a CSTB score for each patient based on the combined CSTB I-III by using the ridge regression analysis. The prognostic performance of CSTB score is assessed by the area under the receiver operating characteristic curve (AUC), Cox proportional hazard regression analysis, as well as Kaplan-Meier survival analysis. Results: As an independent prognostic factor, statistical results reveal that the prognostic performance of CSTB score is better than that of the clinical model combining three independent prognostic indicators, molecular subtype, tumor size, and lymph nodal metastasis (AUC, Training dataset: 0.773 vs. 0.749; External validation: 0.753 vs. 0.724; HR, Training dataset: 4.18 vs. 3.92; External validation: 4.98 vs. 4.16), and as an auxiliary indicator, it can greatly improve the accuracy of prognostic prediction. And furthermore, a nomogram combining the CSTB score with the clinical model is established for prognosis prediction and clinical decision making. Conclusion: This standardized and automated imaging prognosticator may convince pathologists to adopt it as a prognostic factor, thereby customizing more effective treatment plans for patients. [ABSTRACT FROM AUTHOR]

Neoadjuvant chemotherapy has become a standard treatment for breast cancer as it has been shown to increase the rate of breast preservation and to improve outcome in patients. However, how to accurately detect residual tumors is still a challenge. In this work, we tried to use multiphoton imaging to look for residual breast tumors after preoperative therapy. Imaging results demonstrate that multiphoton microscopy can identify remaining tumor tissues and can even detect rarely residual tumor cells, which would be helpful for surgeons to accurately assess the surgical margin in real time to confirm negative margins during operation. We also performed a quantification analysis of the nuclear area of tumor cells before and after treatment with neoadjuvant chemotherapy. The measurement data show that the tumor cell nuclei after chemotherapy are significantly larger than those without treatment, and there is a statistically significant difference in the nuclear areas between the pre-treatment and post-treatment mammary carcinoma. Our pilot study indicates the potential utility of multiphoton imaging for detecting residual breast carcinoma tissues in fresh, ex vivo specimens without the use of exogenous contrast agents. We foresee real-time intraoperative applications of multiphoton microscopy in evaluating therapy response, and thereby helping clinicians develop individualized treatment plans. [ABSTRACT FROM AUTHOR]

Liquid-assisted hard tissue ablation by infrared lasers has extensive clinical application. However, detailed studies are still needed to explore the underlying mechanism. In the present study, the dynamic process of bubble evolution induced by Ho:YAG laser under water without and with bone tissue at different thickness layer were studied, as well as its effects on hard tissue ablation. The results showed that the Ho:YAG laser was capable of ablating hard bone tissue effectively in underwater conditions. The penetration of Ho:YAG laser can be significantly increased up to about 4 mm with the assistance of bubble. The hydrokinetic forces associated with the bubble not only contributed to reducing the thermal injury to peripheral tissue, but also enhanced the ablation efficiency and improve the ablation crater morphology. The data also presented some clues to optimal selection of irradiation parameters and provided additional knowledge of the bubble-assisted hard tissue ablation mechanism. [ABSTRACT FROM AUTHOR]